In the Introduction of the main text, we argue that existing sequential order modeling approaches make CoSOD networks unstable. So we do experiments on two typical methods, including RCAN [1]} and ICNet [2]}, to verify the inferring procedure of these two methods are unstable. Because CoAD [3]} does not release their code, so we can not do experiments on CoAD. During testing, for each image group, we randomize 10 different orders, and the three results are shown in Table.REF . As can be seen in Table.REF , whether using RNN (RCAN), or applying some sophisticated modification on CNNs architectures (ICNet), can not let the CoSOD network insensitive to the input order of group images, leading to an unstable inferring procedure. Because in sequential order modeling, both CNNs and RNNs have inherent deficiencies. Through these experiments, we further verify that the proposed CoSformer greatly improves the stability CoSOD network.
